Find Academic Supervisors

• Logic
• Philosophy of Artificial Intelligence
• Non-Standard Logics
• +3 more

Fabio Aurelio D'Asaro is a Researcher at the Department of Human Sciences , University of Verona. His research focuses on Logic , Non-Standard Logics (non-monotonic, paraconsistent, modal, and probabilistic reasoning), and Explainable AI , with interdisciplinary connections to Philosophy of Science and Computational Epistemology . He explores how transparent AI systems can enhance trust, reliability, and ethical considerations in human-machine interactions, addressing topics like autonomy, control, and moral responsibility. D'Asaro is involved in international collaborations with institutions such as UCL KIDS , Imperial SPIKE , and LUCI Unimi . He also serves as an editor and organizer for journals and conferences on Explainable AI , AI Ethics , and Formal Argumentation . Research Grants : Development of Artificial Intelligence methods to support insurance policy sales (2022–2025) Scientific Awards : Premio italiano di Pedagogia 2025 (SIPED prize) for the book Il feedback a scuola. Strategie per promuovere l'apprendimento Teaching Roles : Big data epistemology (Master's Degree in Data Science) Computational epistemology and philosophy (Master's Degree in Artificial Intelligence) Logic and philosophy of science (Bachelor's Degree in Philosophy) Clinical logic and philosophy of science in physiotherapy (Bachelor's Degree in Physiotherapy programs across Vicenza, Rovereto, and Verona) Committee Memberships : ETHICS COMMITTEE – Human Sciences Research Policy Committee Seminar and Publications Committee

• CAD tools
• Digital architectures
• Emerging technologies
• +9 more

Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.

Fabrizio RiguzziView profile

Professor

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +3 more

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

Stefano FerilliView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Mining
• +6 more

Stefano Ferilli is a Professor of Computer Science at the University of Bari, Italy, where he leads the ARA (Apprendimento e Ragionamento Automatico) research lab within the Department of Computer Science. His academic roles include former Director of the Interdepartmental Center for Logic and Applications (CILA) and current head of the Artificial Intelligence & Intelligent Systems node in the CINI national laboratory. He holds a PhD in Computer Science and has been a key figure in advancing machine learning, logic programming, and digital library technologies. Education: Laurea (MSc equivalent) in Information Sciences (1996), Specialist Laurea in Computer Science (2003), and PhD in Computer Science (2001). His research focuses on foundational aspects of machine learning, multi-strategy reasoning, process mining, and applications in cultural heritage, bioinformatics, and smart environments. Research Contributions: Developed frameworks like INTHELEX (incremental theory learner), WoMan (process mining), and DoMInUS (document management). Over 370 publications, including a Springer monograph and multiple award-winning papers. Active in organizing conferences like ECML-PKDD, ICDM, and IRCDL, and serves on editorial boards of journals like Information Sciences . Projects: Led or participated in over 30 national and European projects, including EU-funded initiatives on digital libraries (COLLATE, DELOS) and AI applications. Collaborates with industries like Samsung and institutions like the Italian Police for traffic analysis and cultural heritage preservation. Awards: Recognized for outstanding peer review (MDPI, ECMLPKDD), best paper awards, and contributions to AI education and cultural heritage. Member of prestigious associations like AI*IA (Italian AI Society) and AICA (Italian Computing Society).

• Logic-in-memory
• Machine learning
• Nanocomputing
• +7 more

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

Elena UmiliView profile

Assistant Professor

• Neurosymbolic AI
• Deep Learning
• Deep Reinforcement Learning
• +3 more

Elena Umili is an Assistant Professor (RTD-A) at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome, specializing in Neurosymbolic AI research. Her work bridges deep learning with symbolic reasoning systems. She received her PhD in Engineering in Computer Science from Sapienza University of Rome in 2023 under the supervision of Prof. Giuseppe De Giacomo and Prof. Roberto Capobianco. Her doctoral thesis focused on 'Discovering Logical Knowledge in Non-Symbolic Domains'. Her research interests center on Neurosymbolic AI integration , particularly: Combining deep machine learning with symbolic reasoning Temporal logic specifications in neural systems Automata learning through neural relaxations Non-Markovian reinforcement learning tasks Visual grounding of logical specifications Analysis of her recent publications reveals a strong focus on neural-symbolic integration where she develops frameworks like DeepDFA and Neural Reward Machines. Her work consistently addresses the challenge of incorporating logical constraints into deep learning systems, with applications spanning robotics, sequence generation, and visual reasoning. The research demonstrates increasing sophistication in handling temporal logic specifications within neural architectures. She is an active member of research groups focused on Artificial Intelligence and Knowledge Representation, as well as Artificial Intelligence and Robotics at Sapienza University. While no formal advisees or major awards are currently documented in her public profile, her recent publications indicate significant contributions to the neurosymbolic AI field through top-tier conferences including ECAI, KR, and specialized workshops. Her work shows strong potential for future impact in bridging the gap between neural and symbolic AI paradigms.

Werner NuttView profile

Professor

• Data Management
• Knowledge Representation
• Intelligent Information Extraction
• +3 more

Werner Nutt is a Professor at the Free University of Bozen-Bolzano , Italy, affiliated with the Faculty of Computer Science since 2005. He previously held academic positions as a Reader at Heriot-Watt University (2000-2005), Visiting Professor at Hebrew University of Jerusalem, and Research Scientist at DFKI (1992-2000). Current Role: Professor, Free University of Bozen-Bolzano Past Roles: Reader (Heriot-Watt), Visiting Professor (Hebrew University), Research Scientist (DFKI) Research Interests focus on Data Management , Knowledge Representation , and Intelligent Information Extraction , with emphasis on modeling Construction Processes and ensuring Data Quality . His work bridges Semantic Web technologies with Business Process Management , notably through the COCkPiT project (2017-present) for construction process optimization. Key Contributions include foundational work on Query Completeness in databases, SPARQL Reasoning , and Semantic Diagnostics . He has published extensively in venues like ISWC , BPM , and CIKM , with an h-index of 35 on Google Scholar. His 154+ publications span topics from Probabilistic XML to Construction Process Modeling .

• Blockchain
• Cybersecurity
• Distributed Systems
• +5 more

Roberto Zunino is an Associate Professor in the Department of Mathematics at the University of Trento, specializing in blockchain technologies, formal methods, and distributed systems. His research bridges theoretical computer science with practical cryptographic applications, particularly in Bitcoin and smart contract ecosystems. His research interests focus on blockchain security , smart contract formalization , and probabilistic verification . Key areas include MEV (Maximal Extractable Value) theory, UTXO-based smart contracts, and computationally sound tokenization. His work combines rigorous mathematical modeling with real-world protocol analysis, emphasizing security guarantees through formal methods. Recent publications demonstrate a strong trend toward theoretical foundations of blockchain economics and security. His 15 most recent papers (2020-2025) analyze MEV formalization, Bitcoin contract liquidity, UTXO scalability, and smart contract language design, revealing deep integration of type theory, game theory, and cryptographic primitives. Zunino actively teaches courses including Informatics , Interactive Theorem Proving (using Lean 4), and Computer Tools for Mathematics . His educational focus emphasizes formal verification, imperative programming foundations, and mathematical logic applications in computer science.

• Process Safety
• Risk Management
• Occupational Safety
• +12 more

Micaela Demichela is a Full Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, where she conducts research and teaches in the fields of process safety, risk management, and occupational safety. She is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Center and the Master's and Continuing Education School. She also serves as vice-coordinator of the MISO (Occupational Safety Engineering) Master's program at the Polytechnic University of Milan and is actively involved in the Doctoral College in Chemical Engineering and Metrology at Politecnico di Torino. Her research interests include process safety, probabilistic risk assessment, safety in the workplace, human and organizational factors in risk analysis, and resilience in industrial systems. She integrates chemical engineering principles with safety science to evaluate the safety status of production lines by combining kinetic and heat transfer data with plant characteristics. Her work spans both fine and basic chemicals sectors and extends to petrochemical industries and international research centers. The recent publications highlight a strong trend toward integrating data-driven methodologies, human factors, and advanced technologies such as human-robot collaboration, Bayesian networks, and prognostics and health management (PHM) to enhance safety and resilience in process industries. Her work increasingly focuses on cyber threats, energy resilience, and decision-making frameworks for industrial safety. Fellow, 3ASI - Association of Environmental, Reliability and Industrial Safety Analysts (2013–2015) President, ESReDA - European Safety, Reliability and Data Association (2012–2014) Associate Editor, Journal of Loss Prevention in the Process Industries (2007–) Associate Editor, Frontiers in Chemical Engineering (2019–) She has supervised numerous PhD students and leads multiple research projects, including ND - Resilience against Cyber Threats, CISC - Collaborative Intelligence for Safety Critical Systems, and several Erasmus+ initiatives such as SAFETY4VET and RE@WBC. She teaches courses such as 'Risk Assessment as Decision Making Tools', 'Advanced Technologies for Risk-Based Decision Making', and 'Occupational Safety Engineering' across various engineering programs. She leads the SAfeR research group and the Applied Biotechnology team at DISAT, and is involved in laboratories including the Biotechnological Laboratory.

Luca SpalazziView profile

Associate Professor

• Computer Science
• Cybersecurity
• Blockchain Technology
• +5 more

Luca Spalazzi is an Associate Professor at the Department of Information Engineering , Università Politecnica delle Marche , Italy. His research spans multiple domains including cybersecurity , blockchain technology , machine learning , and telerehabilitation systems for Parkinson's disease. He applies formal methods to software verification and security analysis, with a focus on real-time systems and distributed architectures . Key research areas: Cybersecurity, Blockchain, Machine Learning, IoT, Formal Verification Recent work: Blockchain-based sustainable supply chains, Zero-Knowledge Proofs, Smartphone health monitoring His publications (2013-2025) demonstrate expertise in malware detection , smart contract verification , and AI-driven health solutions . Articles include BRAIN 2024 workshop organization and RAPIDO system for Parkinson's telerehabilitation.

Sergio GrecoView profile

Professor

• Database Theory
• Data Integration
• Inconsistent Data Processing
• +3 more

Sergio Greco is Full Professor at University of Calabria's DIMES Department, Coordinator of the Computer Engineering Degree, and Vice-president of the Computer Engineering national Group. His research spans database theory, data integration, inconsistent data processing, and computational logic. Research Focus: Development of theoretical frameworks for data management including argumentation frameworks, knowledge base querying under inconsistency, and decentralized learning systems. Recent work integrates machine learning with formal reasoning methods. Honors: Best Paper Award at International Conference on Logic Programming (2020) Best Paper Award at RuleML Symposium (2014) Leads projects on cybersecurity and data management funded by EU and Italian Ministry of Research, coordinating national and international research groups.

• Artificial Intelligence
• Machine Learning
• Abstract Argumentation
• +2 more

Gianvincenzo ALFANO is a Researcher at the Department of Computer Engineering, Modelling, Electronics and Systematics (DIMES) at the University of Calabria. His work focuses on abstract argumentation frameworks, epistemic reasoning, and computational complexity. University: University of Calabria Department: Department of Computer Engineering, Modelling, Electronics and Systematics Academic Rank: Researcher Research Interests: Gianvincenzo specializes in abstract argumentation, exploring formal foundations, complexity analysis, and applications in artificial intelligence. His research spans epistemic reasoning, preference handling, and incremental computation in dynamic knowledge bases. Recent Publications: Over the past two years, he has published extensively on topics such as physics-informed neural networks in federated learning, credulous acceptance in high-order frameworks, and complexity of epistemic argumentation. His work emphasizes formal logic, algorithm design, and uncertainty handling in AI systems.

Maurice ter BeekView profile

Researcher

• Formal Methods
• Software Engineering
• Railway Systems
• +5 more

Maurice ter Beek is a Senior Researcher at the Formal Methods and Tools (FMT) Group of the Institute of Information Science and Technologies (ISTI) , part of the Italian National Research Council (CNR) in Pisa, Italy. He leads the FMT Lab since 2019 and coordinates critical projects like ADVENTURE (railway systems evaluation) and T-LADIES (typeful language adaptation). He serves as Editor-in-Chief of Formal Aspects of Computing and holds editorial roles in journals like Science of Computer Programming . His career spans academic leadership in international conferences (chair of ETAPS 2026 , RSSRail 2025 , etc.) and extensive collaborations in formal methods, railway systems, and software product lines. Research Interests: His work focuses on formal methods applied to industrial critical systems, particularly railways, with expertise in variability modeling, attack-defense trees, contract automata, and team automata. Publications address quantitative analysis of reconfigurable systems model checking for railway safety empirical studies on formal methods security risk modeling collaborative software engineering Scientific Awards: ERCIM Fellowship (2003, 2002) SegraVis Fellowship (2005) Best Paper at SPLC 2019 Best Paper at ICIW 2007 Socrates Grant (EU, 2000-2001) Additional Roles: He is a faculty member of the joint PhD program in Smart Computing (Florence, Pisa, Siena), member of ISTI’s Institute Council, and coordinates CNR’s involvement in the PNRR National Sustainable Mobility Centre . His global engagement includes over 50 conference organizing roles and editorial board memberships.

Mieke MassinkView profile

Researcher

• Formal Methods
• Concurrency Theory
• Process Algebras
• +4 more

Dr. Mieke Massink is a Senior Researcher at the Institute of Information Science and Technologies 'Alessandro Faedo' (ISTI) under the Consiglio Nazionale delle Ricerche (CNR) in Pisa, Italy. Her career spans over three decades with key roles in formal verification, human-computer interaction (HCI), and collective adaptive systems. Research Interests: Formal specification & verification of concurrent systems Spatial/spatio-temporal model checking Collective adaptive systems analysis Stochastic models in user interaction Quantitative extensions of process algebras Recent Publications focus on hybrid AI integration with spatial model checking, polyhedral logic minimization, and scalable verification techniques. Her work bridges formal methods with applications in healthcare and smart environment systems. Projects: Leads EU-NG MUR-PRIN 2022 Stendhal (spatio-temporal logic), MUR-PNRR THE (health ecosystems), and CNR-SRNSF bilateral collaborations. Previously involved in EU-FET QUANTICOL, PRIN CINA, and FP7 ASCENS projects. Teaching: Regularly lectures on Stochastic Model Checking for the PhD Program in Smart Computing (Florence/Pisa/Siena) and has taught formal verification courses at the University of Florence.

• Artificial Intelligence
• Computational Argumentation
• Uncertainty Representation
• +3 more

Pietro Baroni is a Full Professor of Computer Science at the Department of Information Engineering, University of Brescia. His research focuses on artificial intelligence, computational argumentation, uncertainty representation, decision support systems, automated diagnosis, and multi-agent systems. He has authored over 110 scientific papers and holds a patent in his field. Key research interests include formal argumentation frameworks, causal reasoning, and their applications in healthcare robotics, energy systems, and decision-making. His work bridges theoretical foundations (e.g., abstract argumentation semantics) with practical implementations in domains like medical automation and sustainable engineering. Notable contributions include advancing automated diagnosis methods for power grids, developing collaborative robotics for personalized medicine, and integrating user preferences into decision support systems. His recent publications emphasize explainable AI, energy efficiency optimization, and interdisciplinary applications of argumentation theory. Baroni’s research has been applied to real-world challenges such as wastewater treatment optimization and environmental footprint assessment. He actively contributes to academic communities through editorial roles and conference organization, including the Logic and Argumentation (CLAR) conference series.